Abstract

Falls not only present a considerable health threat, but the resulting treatment and loss of working days also place a heavy economic burden on society. Gait instability is a major fall risk factor, particularly in geriatric patients, and walking is one of the most frequent dynamic activities of daily living. To allow preventive strategies to become effective, it is therefore imperative to identify individuals with an unstable gait. Assessment of dynamic stability and gait variability via biomechanical measures of foot kinematics provides a viable option for quantitative evaluation of gait stability, but the ability of these methods to predict falls has generally not been assessed. Although various methods for assessing gait stability exist, their sensitivity and applicability in a clinical setting, as well as their cost-effectiveness, need verification. The objective of this systematic review was therefore to evaluate the sensitivity of biomechanical measures that quantify gait stability among elderly individuals and to evaluate the cost of measurement instrumentation required for application in a clinical setting. To assess gait stability, a comparative effect size (Cohen's d) analysis of variability and dynamic stability of foot trajectories during level walking was performed on 29 of an initial yield of 9889 articles from four electronic databases. The results of this survey demonstrate that linear variability of temporal measures of swing and stance was most capable of distinguishing between fallers and non-fallers, whereas step width and stride velocity prove more capable of discriminating between old versus young (OY) adults. In addition, while orbital stability measures (Floquet multipliers) applied to gait have been shown to distinguish between both elderly fallers and non-fallers as well as between young and old adults, local stability measures (λs) have been able to distinguish between young and old adults. Both linear and nonlinear measures of foot time series during gait seem to hold predictive ability in distinguishing healthy from fall-prone elderly adults. In conclusion, biomechanical measurements offer promise for identifying individuals at risk of falling and can be obtained with relatively low-cost tools. Incorporation of the most promising measures in combined retrospective and prospective studies for understanding fall risk and designing preventive strategies is warranted.

Effect size (ES; presented as Cohen's d) for each linear outcome measure for studies comparing fallers versus non-fallers. The outcome measures are defined with the kinematic parameter measured (e.g. stride time and minimum foot clearance) followed by the mathematical algorithm used to estimate stability indicated in parenthesis (e.g. CV and s.d.). The studies in which the respective measures are included are then indicated in squared brackets next to the outcome measures. For example, stride time (CV) [] indicates that the kinematic parameter analysed was stride time, the mathematical algorithm, CV, was applied to stride time in the study. The error bars indicate the standard deviation (s.d.) of ES across studies. In cases, where the outcome measure was applied in only one study, no error bars are shown. Cohen's d values were classified into four different faller definition categories (cat. 1—cat. 4): studies with at least one fall in the 12 months following data collection (white bars, cat. 1); studies with at least one fall in the 12 months prior to data collection (light grey bars, cat. 2); studies with at least one fall in the 5 years prior to data collection (dark grey bars, cat. 3); and studies with at least one fall in the 13 weeks following data collection (black bars, cat. 4). Asterisk indicates a negative ES, indicating reduced step width variability among fallers [].

Mean ES (presented as Cohen's d) for each nonlinear outcome measure for studies incorporating fallers versus non-fallers comparison. The error bars indicate s.d.s for all cases in which the outcome measure was applied in more than one study. Cohen's d values were classified into three faller definition categories (white bars, cat. 1, grey bars, cat. 2 and black bars, cat. 5): studies with at least one fall in the 12 months following data collection (cat. 1); studies with at least one fall in the 12 months prior to data collection (cat. 2) and studies with at least three falls in the 6 months prior to data collection (cat. 5). Studies using faller definition categories 3 and 4 did not use nonlinear measures.

Mean ES (presented as Cohen's d) for each linear outcome measure for studies incorporating old versus young comparisons. Cohen's d values were classified into four different mean age difference categories: mean age difference less than 40 years; between 40 and less than 45 years (grey bars) between 45 and less than 50 (black bars); and greater than 50.

Mean ES (presented as Cohen's d) for each nonlinear outcome measure for studies incorporating old versus young comparisons. Cohen's d values were classified into three different mean age difference categories: mean age difference between 40 and less than 45 years (light grey bars) between 45 and less than 50 (black bars); and greater than 50 (dark grey bars).